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A research review on a database management system design for child growth and malnutrition monitoring in the Regency of Serdang Bedagai, Indonesia. The paper discusses the problem of stunting and the unavailability of an efficient database to monitor children's physical growth. The authors propose a new database design that enables time-series monitoring of children's physical growth. the three-step design process and the normalization process. It also describes the data dictionary, entity-relationship model, and user views. business rules and the acquired data from monitoring children's growth.
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Bicol University College of Science Special Topics in IT Research Review 2: Database Management System Royland V. Pepaño
Title: Database Management System Design with Time Series Modification for Child Growth and Malnutrition Monitoring in The Regency of Serdang Bedagai
Authors: Reza Rahutomo, Ika Nurlaila, Anzaludin Samsinga Perbangsa, and Bens Pardamean
Proceedings: 2020 International Conference on Information Management and Technology (ICIMTech) DOI: 10.1109/ICIMTech50083.2020.
Summary
The paper focused on implementing the author's database system design to provide an efficient way of handling the data in Child Growth and Malnutrition Monitoring in Serdang Bedagai Regency, Indonesia. The authors created a new database design that enables the time-series monitoring of children's physical growth. The system is based on Connoly and Begg's principles in database system development and was built through a 3-steps design: the conceptual, followed by logical and lastly, the normalizations-enriched physical design to efficiently manage the data being generated by the participants in the monitoring program.
Problem/s
Stunting refers to a child who is too short for his or her age.
The main problem presented in the study is the unavailability of an efficient database in the regency to help the public health office document and monitor children's physical growth in the targeted population. As a consequence, no proper intervention has properly formulated to reverse the bad impact of stunting. Formulating a new database design with time series modification allows the authors to effectively and efficiently monitor every bit of superficial growth increase among participants. The proposed solution was purposely made to provide accountable and consistent data management to achieve the national zero stunting goal.
Solution/s and Simulation/s
The author's database design is comprising of conceptual, logical, and physical designs. It has a data dictionary, a working Entity-Relationship Model (ERM), and user views. The conceptual design precisely formatted the operational activity-based concept, which produces entities, attributes, and relationships needed for ER Modeling. The logical design role is to translate the conceptual design into the logical structures in which the relations between entities are formatted and developed. Lastly, the physical design role is to convert the logical design into physical forms to be implemented in the target Database Management System (DBMS). It's set to define
constraints, cross-reference between entities and technological estimations and create a user view.
The database is referred to as an unnormalized form before normalization. To meet the requirement of 1NF, the authors identified an entity listed in the unnormalized table and dragged it into a different table. Next, the 2NF normalization creates interdependency among key and non-key attributes. Lastly, 3NF normalize the 2NF table without any transitive dependencies. The normalization problems can be solved by separating columns that depend on the table's primary key hence turning into new independent columns encompassing several attributes.
Furthermore, the data dictionary comprises Patient Data Dictionary, Staff Data Dictionary, and Growth Data Dictionary, with each composed with necessary attributes. The three cited dictionaries are comprised with fields such as Attributes, Description, Data Type, and Format with the purpose to get the necessary information needed for the monitoring such as nutrition status of the Patient, symptoms before and after drug intervention, family's background, physical characteristics of the Patient, time records of each Patient, etc.
The ERM provides these business rules:
Patient to Growth (1:M)
Staff to Patient (1:M)
Staff to Growth (1:M)
Staff
The role of the Pediatrician is to access the growth report from the Patient. The role of the Pediatric Officer is to measure the growth examination taken by the Patient. The role of the Registration Officer is to register the Patient's data to Patient Registration.
Moreover, the acquired data from monitoring the children's growth is divided into registration and examination parts. In registration, demography profiles of each child are recorded, including the socio-economic background of the parents. In the examination part, all physical aspects regarding an increment of linear growth are measured, and monthly update is added up to 6 months. The acquired data aims to characterize and map the indications that might be correlative or causative to the stunted condition. The user view has three different viewings. The registration officers,